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Pentangle Tech Services | P5 Group
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AI/ML ENGINEER

Pentangle Tech Services | P5 Group · California, United States

Actively hiring Posted 3 months ago

Job Description & Skill Requirement:

We’re seeking a highly skilled AI/ML Engineer to join our engineering team in USA. his role requires a strong foundation in computer science, statistics, and data science, along with hands-on experience in modern ML frameworks.

Required Experience and Exposure

  • Bachelor’s or master’s degree in computer science, Machine Learning, Business Analytics, Data Science or related field
  • Proven experience in building and deploying ML models in real-world applications
  • Strong programming skills in Python (preferred), Gherkin.
  • Solid understanding of machine learning algorithms, deep learning, and statistical modeling
  • Experience with any of the cloud platforms (AWS or any) and ML tools (Databricks, MLflow, etc.)

Job Duties and Responsibilities:

  • Develop AI-driven solutions and intelligent agents tailored to automotive applications, leveraging Python, Gherkin, C++, and modern AI/ML frameworks across both front-end and back-end systems.
  • Build and implement AI-powered tools to streamline and enhance various stages of automotive testing and validation.
  • Integrate and manage large language models (LLMs) such as Llamas, ChatGPT, and Gemini using AWS Bedrock and Amazon SageMaker for inference, deployment, and fine-tuning.
  • Fine-tune LLMs and AI models to optimize performance and accuracy for domain-specific automotive use cases.
  • Deploy, monitor, and maintain AI systems in production environments, ensuring reliability, scalability, and compliance.
  • Collaborate closely with cross-functional teams—including data scientists, HIL testers, and feature owners—to embed AI capabilities into automotive system architectures.

Required Skills:

  • Programming: Python, Exposure to C++

  • Behavior Driven Development: Gherkin

  • Cloud Platforms: AWS

  • Cloud Services: AWS Bedrock and Amazon SageMaker

Preferred Skills:

  • ML Frameworks: (Example: TensorFlow, PyTorch, Scikit-learn)

  • Data Management and Analysis: (Example: SQL, Spark, Pandas)

  • Devops/ Deployment: exposure to Docker or Kubernetes, CI/CD pipeline etc

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Fulltime Ai Engineer Machine Learning Deep Learning Data Science Ai
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